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Authors: Tim Schopf ; Simon Klimek and Florian Matthes

Affiliation: Department of Informatics, Technical University of Munich, Boltzmannstrasse 3, Garching, Germany

Keyword(s): Natural Language Processing, Keyphrase Extraction, Pretrained Language Models, Part of Speech.

Abstract: Keyphrase extraction is the process of automatically selecting a small set of most relevant phrases from a given text. Supervised keyphrase extraction approaches need large amounts of labeled training data and perform poorly outside the domain of the training data (Bennani-Smires et al., 2018). In this paper, we present PatternRank, which leverages pretrained language models and part-of-speech for unsupervised keyphrase extraction from single documents. Our experiments show PatternRank achieves higher precision, recall and F1 -scores than previous state-of-the-art approaches. In addition, we present the KeyphraseVectorizers package, which allows easy modification of part-of-speech patterns for candidate keyphrase selection, and hence adaptation of our approach to any domain.

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Paper citation in several formats:
Schopf, T.; Klimek, S. and Matthes, F. (2022). PatternRank: Leveraging Pretrained Language Models and Part of Speech for Unsupervised Keyphrase Extraction. In Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KDIR; ISBN 978-989-758-614-9; ISSN 2184-3228, SciTePress, pages 243-248. DOI: 10.5220/0011546600003335

@conference{kdir22,
author={Tim Schopf. and Simon Klimek. and Florian Matthes.},
title={PatternRank: Leveraging Pretrained Language Models and Part of Speech for Unsupervised Keyphrase Extraction},
booktitle={Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KDIR},
year={2022},
pages={243-248},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011546600003335},
isbn={978-989-758-614-9},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KDIR
TI - PatternRank: Leveraging Pretrained Language Models and Part of Speech for Unsupervised Keyphrase Extraction
SN - 978-989-758-614-9
IS - 2184-3228
AU - Schopf, T.
AU - Klimek, S.
AU - Matthes, F.
PY - 2022
SP - 243
EP - 248
DO - 10.5220/0011546600003335
PB - SciTePress

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